corda/docs/source/node-administration.rst

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Node administration
===================
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When a node is running, it exposes an RPC interface that lets you monitor it,
you can upload and download attachments, access a REST API and so on. A bundled
Jetty web server exposes the same interface over HTTP.
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Logging
-------
By default the node log files are stored to the ``logs`` subdirectory of the working directory and are rotated from time
to time. You can have logging printed to the console as well by passing the ``--log-to-console`` command line flag.
The default logging level is ``INFO`` which can be adjusted by the ``--logging-level`` command line argument. This configuration
option will affect all modules.
It may be the case that you require to amend the log level of a particular subset of modules (e.g. if you'd like to take a
closer look at hibernate activity). So, for more bespoke logging configuration, the logger settings can be completely overridden
with a `Log4j 2 <https://logging.apache.org/log4j/2.x>`_ configuration file assigned to the ``log4j.configurationFile`` system property.
Example
+++++++
Create a file ``sql.xml`` in the current working directory. Add the following text :
.. code-block:: xml
<?xml version="1.0" encoding="UTF-8"?>
<Configuration status="WARN">
<Appenders>
<Console name="Console" target="SYSTEM_OUT">
<PatternLayout pattern="%d{HH:mm:ss.SSS} [%t] %-5level %logger{36} - %msg%n"/>
</Console>
</Appenders>
<Loggers>
<Logger name="org.hibernate" level="debug" additivity="false">
<AppenderRef ref="Console"/>
</Logger>
<Root level="error">
<AppenderRef ref="Console"/>
</Root>
</Loggers>
</Configuration>
Note the addition of a logger named ``org.hibernate`` that has set this particular logger level to ``debug``.
Now start the node as usual but with the additional parameter ``log4j.configurationFile`` set to the filename as above, e.g.
``java <Your existing startup options here> -Dlog4j.configurationFile=sql.xml -jar corda.jar``
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To determine the name of the logger, for Corda objects, use the fully qualified name (e.g. to look at node output
in more detail, use ``net.corda.node.internal.Node`` although be aware that as we have marked this class ``internal`` we
reserve the right to move and rename it as it's not part of the public API as yet). For other libraries, refer to their
logging name construction. If you can't find what you need to refer to, use the ``--logging-level`` option as above and
then determine the logging module name from the console output.
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Database access
---------------
The node exposes its internal database over a socket which can be browsed using any tool that can use JDBC drivers.
The JDBC URL is printed during node startup to the log and will typically look like this:
``jdbc:h2:tcp://192.168.0.31:31339/node``
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The username and password can be altered in the :doc:`corda-configuration-file` but default to username "sa" and a blank
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password.
Any database browsing tool that supports JDBC can be used, but if you have IntelliJ Ultimate edition then there is
a tool integrated with your IDE. Just open the database window and add an H2 data source with the above details.
You will now be able to browse the tables and row data within them.
Monitoring your node
--------------------
Like most Java servers, the node exports various useful metrics and management operations via the industry-standard
`JMX infrastructure <https://en.wikipedia.org/wiki/Java_Management_Extensions>`_. JMX is a standard API
for registering so-called *MBeans* ... objects whose properties and methods are intended for server management. It does
not require any particular network protocol for export. So this data can be exported from the node in various ways:
some monitoring systems provide a "Java Agent", which is essentially a JVM plugin that finds all the MBeans and sends
them out to a statistics collector over the network. For those systems, follow the instructions provided by the vendor.
.. warning:: As of Corda M11, Java serialisation in the Corda node has been restricted, meaning MBeans access via the JMX
port will no longer work. Please use java agents instead, you can find details on how to use Jolokia JVM
agent `here <https://jolokia.org/agent/jvm.html>`_.
`Jolokia <https://jolokia.org/>`_ allows you to access the raw data and operations without connecting to the JMX port
directly. The nodes export the data over HTTP on the ``/jolokia`` HTTP endpoint, Jolokia defines the JSON and REST
formats for accessing MBeans, and provides client libraries to work with that protocol as well.
Here are a few ways to build dashboards and extract monitoring data for a node:
* `JMX2Graphite <https://github.com/logzio/jmx2graphite>`_ is a tool that can be pointed to /monitoring/json and will
scrape the statistics found there, then insert them into the Graphite monitoring tool on a regular basis. It runs
in Docker and can be started with a single command.
* `JMXTrans <https://github.com/jmxtrans/jmxtrans>`_ is another tool for Graphite, this time, it's got its own agent
(JVM plugin) which reads a custom config file and exports only the named data. It's more configurable than
JMX2Graphite and doesn't require a separate process, as the JVM will write directly to Graphite.
* Cloud metrics services like New Relic also understand JMX, typically, by providing their own agent that uploads the
data to their service on a regular schedule.
* `Telegraf <https://github.com/influxdata/telegraf>`_ is a tool to collect, process, aggregate, and write metrics.
It can bridge any data input to any output using their plugin system, for example, Telegraf can
be configured to collect data from Jolokia and write to DataDog web api.
Memory usage and tuning
-----------------------
All garbage collected programs can run faster if you give them more memory, as they need to collect less
frequently. As a default JVM will happily consume all the memory on your system if you let it, Corda is
configured with a relatively small 200mb Java heap by default. When other overheads are added, this yields
a total memory usage of about 500mb for a node (the overheads come from things like compiled code, metadata,
off-heap buffers, thread stacks, etc).
If you want to make your node go faster and profiling suggests excessive GC overhead is the cause, or if your
node is running out of memory, you can give it more by running the node like this:
``java -Xmx1024m -jar corda.jar``
The example command above would give a 1 gigabyte Java heap.
.. note:: Unfortunately the JVM does not let you limit the total memory usage of Java program, just the heap size.